The overall long-term goal of this project is to assess the value of multimodality imaging for (1) differential diagnosis and early detection of FTD subtypes and related disorders, (2) for understanding the changes in the brain responsible for cognitive, linguistic, and emotional dysfunction in FTD and AD, and (3) to predict longitudinal changes in cognition and function in FTD. These goals will be accomplished by utilizing an integrated processing framework for multimodality neuroimages as well as modern multivariate statistical methods that allow simultaneous testing of variations across image modalities and across brain regions for maximally exploiting information from multimodality brain images. Specific Aims are to: (1) Use multimodality neuroimaging to distinguish those subjects with non-AD clinical syndromes caused by Alzheimer's amyloid pathology from those without amyloid pathology. We hypothesize that although the changes of sMRI will be the dominant imaging features for differential diagnosis at later stages of disease, adding ASL, DTI, ICN fMRI, FDG PET will improve single subject prediction of subjects with FTD clinical syndromes associated with amyloid pathology determined by PIB imaging versus those associated with other pathologies. (2) Explore the brain-behaviour association of multimodality neuroimaging for the following cognitive and behavioral profiles: (a) motor speech impairment, (b) executive control, and (c) emotion. (3) Explore the predictive value of baseline brain-behavior associations for longitudinal decline and identify a combination of multimodality brain-behavior associations that best predicts the decline. The predictors will be various brain regions in the different imaging modalities and the outcomes will be the rate of change of cognitive function measured by CDR sum of boxes. The innovative nature of this project is the use of multimodality-multivariate analysis methods to investigate FTD and related neurodegenerative diseases. The long term significance of this project is that as these methods are developed, they will be used to explore improved methods for early detection, diagnosis, and monitoring of change, and ultimately will lead to improved patient assessment and development of improved treatments.